Rapid patient-specific FEM meshes from 3D smart-phone based scans

Area of Science:

• Biomedical Engineering
• Medical Imaging

Background:

• Accurate finite element method (FEM) meshes are crucial for precise thoracic electrical impedance tomography (EIT) imaging.
• Current methods for generating subject-specific meshes can be time-consuming and complex.

Purpose of the Study:

• To describe and evaluate a novel smartphone-based approach for rapid generation of subject-specific FEM meshes.
• To assess the potential of these meshes to enhance the accuracy of thoracic EIT images.

Main Methods:

• Utilized an iPhone app (Heges) for 3D scanning, a custom belt, and open-source software to create subject-specific meshes.
• Validated the method quantitatively using mannequin and volunteer tests with an infrared tracker.
• Qualitatively assessed image quality from tidal-breathing EIT in nine subjects.

Main Results:

• Subject-specific meshes generated in under 7 minutes with minimal user interaction (average 3.4 minutes).
• Mannequin tests showed high precision (3.2 ± 0.4 mm RMSE) and accuracy (4.0 ± 0.3 mm RMSE).
• Volunteer tests demonstrated practical accuracy (5.2 ± 2.1 mm RMSE precision, 7.7 ± 2.9 mm RMSE accuracy).

Conclusions:

• Smartphone-based FEM mesh generation is feasible and efficient for thoracic EIT.
• This method has the potential to reduce geometric artifacts and improve EIT's clinical applicability.